...they’re ants. That’s just not how ants work. For a myriad of reasons. The whole point of the post is that there isn’t necessarily local deliberative intent, just strategies filling ecological niches.
gallabytes(Jack Gallagher)
Karma: 174
Of course, if you don’t like how an exponential curve fits the data, you can always change models—in this case, probably to a curve with 1 more free parameter (indicating a degree of slowdown of the exponential growth) or 2 more free parameters (to have 2 different exponentials stitched together at a specific point in time).
Oh that’s actually a pretty good idea. Might redo some analysis we built on top of this model using that.
correct. edited to make this more obvious
This argument would make much more sense in a just world. Information that should damage someone is very different from information that will damage someone. With blackmail you’re optimized to maximize damage to the target, and I expect tails to mostly come apart here. I don’t see too many cases of blackmail replacing MeToo. When was the last time the National Enquirer was a valuable whistleblower?
EDIT: fixed some wording
When trying to fit an exponential curve, don’t weight all the points equally
We didn’t. We fit a line in log space, but weighted the points by sqrt(y). The reason we did that is because it doesn’t actually appear linear in log space.
This is what it looks like if we don’t weight them. If you want to bite the bullet of this being a better fit, we can bet about it.
How rapidly are GPUs improving in price performance?
I’d optimize more for not making enemies or alienating people than for making people realize how bad the situation is or joining your cause.
Why isn’t this a fully general argument for never rocking the boat?
Based on my models (such as this one), the chance of AGI “by default” in the next 50 years is less than 15%, since the current rate of progress is not higher than the average rate since 1945, and if anything is lower (the insights model linked has a bias towards listing recent insights).
Both this comment and my other comment are way understating our beliefs about AGI. After talking to Jessica about it offline to clarify our real beliefs rather than just playing games with plausible deniability, my actual probability is between 0.5 and 1% in the next 50 years. Jessica can confirm that hers is pretty similar, but probably weighted towards 1%.
I think I’m more skeptical than you are that it’s possible to do much better (i.e., build functional information-processing institutions) before the world changes a lot for other reasons (e.g., superintelligent AIs are invented)
Where do you think the superintelligent AIs will come from? AFAICT it doesn’t make sense to put more than 20% on AGI before massive international institutional collapse, even being fairly charitable to both AGI projects and prospective longevity of current institutions.
When considering an embedder , in universe , in response to which SADT picks policy , I would be tempted to apply the following coherence condition:
(all approximately of course)
I’m not sure if this would work though. This is definitely a necessary condition for reasonable counterfactuals, but not obviously sufficient.
I’m fairly interested but don’t really want to be around children.
Asymptotic Decision Theory
By censoring I mean a specific technique for forcing the consistency of a possibly inconsistent set of axioms.
Suppose you have a set of deduction rules over a language . You can construct a function that takes a set of sentences and outputs all the sentences that can be proved in one step using and the sentences in . You can also construct a censored by letting .
A new proposal for logical counterfactuals
I feel like this comment belongs on the LessWrong 2.0 article (to the point that I assumed that’s where it was when I was told about it), but it doesn’t actually matter.
I’d be interested to read another take on it if there’s some novel aspect to the explanation. Do you have a particular approach to explaining it that you think the world doesn’t have enough of?
The tournament definitely made for an interesting game, but more as a conversation starter than a game itself. I suspect part of the issue was how short this particular game was, but the constant cooperation got old pretty quickly. Some ideas for next time someone wants to run a dilemma tournament:
1) Bracket play—you play with another person until one of you defects while the other cooperates. Example round: both cooperate, both cooperate both defect, both defect, player 1 defects and player 2 cooperates, player 1 moves on. This has a trivial vulnerability in that always defecting always wins or ties, so there’d have to be some other incentive to encourage cooperation.
2) Factions—each person is part of a faction, you have some minor term for the total utility of your faction at the end of the game. You could go further with this and have a negative (even more minor) term for the total utility of other factions, or maybe add the option of giving points to other players.
Unrelated note: In the future there should probably be some coordination around walking to/from. While nothing happened this time, Civic Center did not feel like the safest place to be walking around alone late at night.
I doubt there is a sharp distinction between them
Actually, let’s taboo weak and strong AI for a moment.
By weak AI I mean things like video game AI, self driving cars, WolframAlpha, etc.
By strong AI I think I mean something that can create weak AIs to solve problems. Something that does what I mean by this likely includes a general inference engine. While a self driving car can use its navigation programs to figure out lots of interesting routes from a to b, if you tell it to go from California to Japan it won’t start building a boat
What’s your reason for thinking weak AI leads to strong AI? Generally, weak AI seems to take the form of domain-specific creations, which provide only very weak general abstractions.
One example that people previously thought would lead to general AI was chess playing. And sure, the design of chess playing AI forced some interesting development of efficient traversing of large search spaces, but as far as I can tell it has only done so in a very weak way, and hasn’t contributed meaningfully to anything resembling the efficiency of human-style chunking.
Even with that as the goal this model is useless—social distancing demonstrably does not lead to 0 new infections. Even Wuhan didn’t manage that, and they were literally welding people’s doors shut.